Rapid operational analysis application for supply chain management

Abstract

An improved industrial process includes: receiving in a processor a plurality of data items related to an industrial process, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time; analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable; setting a statistical control parameter as an achievable quantity for the at least one variable; identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define at least one excess; and eliminating the at least one excess by shifting resources or altering the process related to the at least one quantity, the shifting or altering being a function of the analyzing of the plurality of data items. Methods related to achievable opportunities for improvement and to identifying contributing factors are also provided.

1 - 18 . (canceled) 
     
     
         19 . A method for improving an industrial process data comprising:
 receiving in a processor a plurality of data items related to an industrial process utilizing parts, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time;   analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable, the at least one variable being a number of defects of the parts;   setting a statistical control parameter as an achievable quantity for the at least one variable;   identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define an excess; and   adding the excesses so as to define an achievable excess reduction amount for the number of defects of the parts of the industrial process.   
     
     
         20 . The method as recited in  claim 19  wherein the at least one variable is the number of defects within a time period. 
     
     
         21 . The method as recited in  claim 19  wherein the statistical control parameter is based on standard deviations from the mean value. 
     
     
         22 . The method as recited in  claim 19  wherein the statistical control parameter is a function of past performance of the industrial process. 
     
     
         23 . The method as recited in  claim 19  wherein the statistical control parameter is dynamic. 
     
     
         24 . An improved industrial process comprising:
 receiving in a processor a plurality of data items related to an industrial process utilizing parts, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time;   analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable, the at least one variable being a number of defects of the parts;   setting a statistical control parameter as an achievable quantity for the at least one variable;   identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define at least one excess; and   eliminating the at least one excess to reduce the number of defects of the parts by shifting resources or altering the process related to the at least one quantity, the shifting or altering being a function of the analyzing of the plurality of data items.   
     
     
         25 . The improved industrial process as recited in  claim 24  wherein the excess is eliminated by shifting resources. 
     
     
         26 . The improved industrial process as recited in  claim 24  wherein due to the shifting, the at least one variable related to a time period decreases, and the at least one variable related to a further time period increases, the at least one variable related to the time period and the at least one variable related to the further time period both remaining under the statistical control parameter. 
     
     
         27 . The improved industrial process as recited in  claim 26  wherein the shifting is a function of a second statistical control parameter, the at least one variable being less than the second statistical control parameter before the shifting. 
     
     
         28 . The improved industrial process as recited in  claim 25  wherein the shifting is a function of a second statistical control parameter, the at least one variable being less than the second statistical control parameter before the shifting. 
     
     
         29 . The improved industrial process as recited in  claim 25  wherein the shifting or altering occurs stepwise in a control loop. 
     
     
         30 . The improved industrial process as recited in  claim 29  wherein the at least one excess includes a plurality of excesses, the shifting or altering eliminating the excesses. 
     
     
         31 . The improved industrial process as recited in  claim 29  wherein the at least one excess includes a plurality of excesses, the shifting or altering eliminating all excesses. 
     
     
         32 . A system for an improved industrial process comprising:
 a processor capable of receiving a plurality of data items related to an industrial process utilizing parts, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time;   an analyzer analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable, the at least one variable being a number of defects of the parts;   an input for setting a statistical control parameter as an achievable quantity for the at least one variable;   the processor identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define an excess;   the system eliminating the excess for the number of defects of the parts of the industrial process by having shifting resources or an altered the process related to the at least one quantity, the shifting or altering being a function of the analyzing of the plurality of data items.